Exoplanets are revolutionizing planetary science by enabling statistical studies of a large number of planets. Empirical measurements of planet occurrence rates inform our understanding of the ubiquity and efficiency of planet formation, while the identification of sub-populations and trends in the distribution of observed exoplanet properties provides insights into the formation and evolution processes that are sculpting distant Solar Systems. In this paper, we review the current best estimates of planet populations. We focus in particular on η⊕, the occurrence rate of habitable zone rocky planets, since this factor strongly influences the design of future space based exoplanet direct detection missions.

We describe multi-baseline observations of a geostationary satellite using the Navy Precision Optical Interferometer (NPOI) during the glint season of March 2015. We succeeded in detecting DirecTV-7S with an interferometer baseline length of 8.8 m on two nights, with a brief simultaneous detection at 9.8 m baseline length on the second night. These baseline lengths correspond to a resolution of ~4 m at geostationary altitude. This is the first multiple-baseline interferometric detection of a satellite.

This paper addresses how the image processing steps involved in computational imaging can be adapted to specific image-based recognition tasks, and how significant reductions in computational complexity can be achieved by leveraging the recognition algorithm's robustness to defocus, poor exposure, and the like. Unlike aesthetic applications of computational imaging, recognition systems need not produce the best possible image quality, but instead need only satisfy certain quality thresholds that allow for reliable recognition. The paper specifically addresses light field processing for barcode scanning, and presents three optimizations which bring light field processing within the complexity limits of low-powered embedded processors.

Industrial and petrochemical facilities present unique challenges for fire protection and safety. Typical scenarios include detection of an unintended fire in a scene, wherein the scene also includes a flare stack in the background. Maintaining a high level of process and plant safety is a critical concern. In this paper, we present a failsafe industrial flame detector which has significant performance benefits compared to current flame detectors. The design involves use of microbolometer in the MWIR and LWIR spectrum and a dual band filter. This novel flame detector can help industrial facilities to meet their plant safety and critical infrastructure protection requirements while ensuring operational and business readiness at project start-up.

Over the next decade, NASA’s Astrophysics Division expects to undertake robotic or unmanned space flight missions that will explore the nature of the universe at its largest scales, its earliest moments, and its most extreme conditions. Current innovative and maturation technology programs are being conducted by NASA’s Astrophysics Division to fill the technology gaps identified by the community. One of these efforts was to establish the Strategic Astrophysics Technology (SAT) program to support the maturation of key technologies. In this paper, these technology programs are described; in particular the SAT program will be presented describing the process to establish priorities, the technology management components, and the efforts to move these technologies into mission concepts and flight missions. The technology roadmap for a large mission concept such as ATLAST is presented as an example of the technology gaps derived and identified from these analyses, which could focus future efforts and investment priorities. Finally, the NASA preparation for the next decade, which will study and mature four large mission concepts, is briefly outlined.

Gallium nitride (GaN) being one of a few piezoelectric semiconductors with low acoustic loss is a perfect material for electro-acoustic applications. Interactions of electrons and phonons are facilitated by the piezoelectric effect in addition to the deformation coupling in GaN, a property that can be used to implement a variety of very interesting devices and metamaterials, such as resonant transistors, acoustic amplifiers, circulators, and couplers. This talk covers theoretical basis of such devices and overviews recent advances in this technology.

Narrow-linewidth lasers are a key component of photonic microwave signal generators, as the width of the generated RF signal is equal to the beat note of used lasers. Heterogeneous silicon photonics platform opens up a possibility of improving the coherence of fully integrated photonic microwave generators by providing means to separate the photon resonator and absorbing active medium; improving the total Q factor of the laser cavity and providing the control of the spontaneous emission into the lasing mode. Further improvement in the laser linewidth is possible by using ring resonators inside the laser cavity. Using the rings inside the cavity benefits the linewidth in two ways: (1) resonance cavity length enhancement and (2) negative optical feedback. The combined effect allows for record linewidth performance as was recently demonstrated: widely-tunable fully monolithically-integrated semiconductor lasers with 50 kHz integrated linewidths. We further theoretically predict that at least an order of magnitude better performance is achievable and that sub-kHz linewidths should be obtainable using low-loss silicon waveguide platform with ~0.5 dB/cm of loss. Heterogeneous platform further complements the microwave signal generator with demonstrated highspeed modulators with 74 GHz bandwidth and detectors with 12 dBm output power at 40 GHz. The InP-based modified uni-traveling carrier photodiodes on SOI waveguides have the highest reported output power levels at multi-GHz frequencies for any waveguide photodiode technology including native InP, Ge/Si, and heterogeneously integrated photodiodes.

RF photonic systems place extremely high demands on optical component performance. To achieve this, a low noise, high power optical source, a high power, linear and low Vπ optical modulator, sharp and uniform optical filters and high saturation power photodetectors are required. While some of these individual components exist, they have not, to date, been integrated in any currently existing monolithic or hybrid photonic integration platform. In this paper, recent advances in discrete component performance is presented, including optical sources, modulators and detectors. In addition, options for the integration of these components onto an integrated photonic platform is reviewed.

The long range objectives of this research are to develop and demonstrate the use of graphene-nanoparticle composites as a high sensitivity, rapid response electronic nose for gas sensing in energy applications. Graphene based device structures suitable for temperatures as high as 1000 °C are targeted. The scope of work includes: a) development of procedures for controllable nucleation and growth of nanoparticles on graphene surfaces, b) fabrication graphene-nanoparticle composite sensors, c) measurement of electrical properties of graphene-nanoparticle composites, and d) determination of sensor characteristics (selectivity and sensitivity). The graphene films are synthesized on 6H-SiC (0001) surfaces using a halogen based plasma etching followed by rapid thermal annealing in atmospheric pressure Ar or under ultrahigh vacuum conditions. Lithography free methods are then used to produce simple sensor structures consisting of interdigitated fingers. This is followed by the nucleation of either Ag, Au, Pt, or Ir nanoparticles on the graphene surfaces using solution based techniques. Atomic force microscopy is used to characterize the particle size distribution of the nucleated nanoparticles. Electrical properties of the graphene and graphenenanoparticle composites are characterized using two point current-voltage measurements. Gas sensor response as a function of temperature is characterized for H2 in Ar gas mixtures.

We report a new distributed fiber optic sensing technique using optical carrier based microwave interferometry. The concept has been demonstrated using different types of optical fibers including singlemode fiber, multimode fiber, single crystal sapphire fiber and polymer fiber. Using the microwave-photonic technique, many fiber interferometers with the same or different optical path differences were interrogated and their locations could be unambiguously determined. The distributed sensing capability was demonstrated using cascaded low-finesse Fabry-Perot interferometers fabricated by fs laser micromachining. Spatially continuous, fully distributed temperature and strain measurements were used as examples to demonstrate the capability of the proposed concept.

Optical fiber pH sensors functionalized with a gold nanoparticle (AuNP)/porous silica film were developed. The transmission of light through the fiber is affected by the change in the refractive index of the porous silica-based nanocomposite coated film as ionic species are concentrated into the coating film when the silica surface becomes negatively charged with increasing pH. To investigate the dependence of the response on the ionic species in solution, we report the optical response of Au/silica film coated fibers in a variety of salt solutions. The response is indeed sensitive to different ionic species in solution. The details of the response are likely also sensitive to the microstructure of the porous silica-based sensing layer.

Consumer electronics account for the majority of electronics manufactured today. Given the temperature limits of humans, consumer electronics are typically rated for operation from -40°C to +85°C. Military applications extend the range to -65°C to +125°C while underhood automotive electronics may see +150°C. With the proliferation of the Internet of Things (IoT), the goal of instrumenting (sensing, computation, transmission) to improve safety and performance in high temperature environments such as geothermal wells, nuclear reactors, combustion chambers, industrial processes, etc. requires sensors, electronics and packaging compatible with these environments. Advances in wide bandgap semiconductors (SiC and GaN) allow the fabrication of high temperature compatible sensors and electronics. Integration and packaging of these devices is required for implementation into actual applications. The basic elements of packaging are die attach, electrical interconnection and the package or housing. Consumer electronics typically use conductive adhesives or low melting point solders for die attach, wire bonds or low melting solder for electrical interconnection and epoxy for the package. These materials melt or decompose in high temperature environments. This paper examines materials and processes for high temperature packaging including liquid transient phase and sintered nanoparticle die attach, high melting point wires for wire bonding and metal and ceramic packages. The limitations of currently available solutions will also be discussed.

We have reported SiC integrated circuits (IC’s) with two levels of metal interconnect that have demonstrated prolonged operation for thousands of hours at their intended peak ambient operational temperature of 500 °C [1, 2]. However, it is recognized that testing of semiconductor microelectronics at temperatures above their designed operating envelope is vital to qualification. Towards this end, we previously reported operation of a 4H-SiC JFET IC ring oscillator on an initial fast thermal ramp test through 727 °C [3]. However, this thermal ramp was not ended until a peak temperature of 880 °C (well beyond failure) was attained. Further experiments are necessary to better understand failure mechanisms and upper temperature limit of this extreme-temperature capable 4H-SiC IC technology. Here we report on additional experimental testing of custom-packaged 4H-SiC JFET IC devices at temperatures above 500 °C. In one test, the temperature was ramped and then held at 727 °C, and the devices were periodically measured until electrical failure was observed. A 4H-SiC JFET on this chip electrically functioned with little change for around 25 hours at 727 °C before rapid increases in device resistance caused failure. In a second test, devices from our next generation 4H-SiC JFET ICs were ramped up and then held at 700 °C (which is below the maximum deposition temperature of the dielectrics). Three ring oscillators functioned for 8 hours at this temperature before degradation. In a third experiment, an alternative die attach of gold paste and package lid were used, and logic circuit operation was demonstrated for 143.5 hours at 700 °C.

The rapid and exponential advances in micro- and nanotechnologies over the last decade have enabled devices that communicate directly with the nervous system to measure and influence neural activity. Many of the earliest implementations focused on restoration of sensory and motor function, but as knowledge of physiology advances and technology continues to improve in accuracy, precision, and safety, new modes of engaging with the autonomic system herald an era of health restoration that may augment or replace many conventional pharmacotherapies. DARPA’s Biological Technologies Office is continuing to advance neurotechnology by investing in neural interface technologies that are effective, reliable, and safe for long-term use in humans. DARPA’s Hand Proprioception and Touch Interfaces (HAPTIX) program is creating a fully implantable system that interfaces with peripheral nerves in amputees to enable natural control and sensation for prosthetic limbs. Beyond standard electrode implementations, the Electrical Prescriptions (ElectRx) program is investing in innovative approaches to minimally or non-invasively interface with the peripheral nervous system using novel magnetic, optogenetic, and ultrasound-based technologies. These new mechanisms of interrogating and stimulating the peripheral nervous system are driving towards unparalleled spatiotemporal resolution, specificity and targeting, and noninvasiveness to enable chronic, human-use applications in closed-loop neuromodulation for the treatment of disease.

Recent technological developments have given neuroscientists direct access to neural signals in real time, with the accompanying ability to decode the resulting information and control various prosthetic devices and gain insight into deeper aspects of cognition. These developments - along with deep brain stimulation for Parkinson's disease and the possible use of electro-stimulation for other maladies - leads to the conclusion that the widespread use electronic brain interface technology is a long term possibility. This talk will summarize the various technical challenges and approaches that have been developed to wirelessly communicate with the brain, including technology constraints, dc power limits, compression and data rate issues.

Retinal prosthesis have been translated to clinical use over the past two decades. Currently, two devices have regulatory approval for the treatment of retinitis pigmentosa and one device is in clinical trials for treatment of age-related macular degeneration. These devices provide partial sight restoration and patients use this improved vision in their everyday lives to navigate and to detect large objects. However, significant vision restoration will require both better technology and improved understanding of the interaction between electrical stimulation and the retina. In particular, current retinal prostheses do not provide peripheral visions due to technical and surgical limitations, thus limiting the effectiveness of the treatment. This paper reviews recent results from human implant patients and presents technical approaches for peripheral vision.

Since 1992, military medicine has considered the relevance, sustainability, and promise of telemedicine in the context of its mission and obligations for service members at home and in war zones. The US Army telemedicine program covers 22 time zones and generates over 5000 tele-consults per month for over 20 medical specialties. More recently the advances in mobile computing and increased adoption of the Smartphone with evolving capabilities for imaging and body-worn sensor integration has emerged in the field called mobile health, or mHealth. This presentation highlights the first 10 years of the U.S. Army mHealth program and includes how similar technologies have translated to wide-scale civilian health care implementation, including a relevant project for Veterans at the University of Pittsburgh. Examples include the successful US Army “mCare” program developed to augment soldier rehabilitation management with USbased geographically dispersed providers that utilizes secure mobile messaging and the soldier’s own cell phone. Additional research interests will describe the use of smartphones on the battlefield enabling capture of operational medical data to improve casualty evacuation and outcome. A DoD-funded traumatic brain injury research project developed for Veterans at the University of Pittsburgh includes a mobile health application that demonstrates the effectiveness of communicating with patients through their personal mobile devices with care managers. Preliminary data for all the projects presented are encouraging for adoption and utilization of a mobile telemedicine platform to meet the complex needs of casualties injured or recovering from a broad range of injuries in unique geographic settings.

We introduce a portable, easy-to-use, worldwide accessible (i.e., web-based), and comprehensive tele-medical visual performance assessment system – the Ceeable Visual Field Analyzer (CVFATM) – for warfighters, pilots, veterans, and civilians to: (1) Accurately and rapidly assess visual performance; (2) characterize visual performance and ocular conditions; and (3) detect the onset of ocular conditions to allow for timely countermeasures as well as patient follow-up over time. CVFA has been shown to be effective in multiple clinical studies. The technology is rapid (< 5 minutes per eye), easy (use of touchscreen), accurate (spatial resolution < 1 degree), non-invasive, and comprehensive. The system automatically characterizes visual field defects in real time to generate new diagnostic insight. The visual performance assessment system is readily adaptable to traditional clinical and non-clinical settings (e.g., in forward operating bases in the theatre). It is capable of rapidly assessing conditions affecting the visual performance of warfighters in the field, allowing for triage and timely application of therapeutic countermeasures. The enabling technologies are a low-cost tablet computer and Internet connection. Ceeable is deploying the technology on a global basis to patients who will benefit from monitoring changes in visual function.

Long-duration missions bring numerous risks that must be understood and mitigated in order to keep astronauts healthy, rather than treat a diagnosed health disorder. Having a limited medical support from mission control center on space exploration missions, crew members need a personal health-tracking tool to predict and assess his/her health risks if no preventive measures are taken. This paper refines a concept employing technologies from Prognostics and Health Management (PHM) for systems, namely real-time health monitoring and condition-based health maintenance with predictive diagnostics capabilities. Mapping particular PHM-based solutions to some Human Health and Performance (HH&P) technology candidates, namely by NASA designation, the Autonomous Medical Decision technology and the Integrated Biomedical Informatics technology, this conceptual paper emphasize key points that make the concept different from that of both current conventional medicine and telemedicine including space medicine. The primary benefit of the technologies development for the HH&P domain is the ability to successfully achieve affordable human space missions to Low Earth Orbit (LEO) and beyond. Space missions on the International Space Station (ISS) program directly contribute to the knowledge base and advancements in the HH&P domain, thanks to continued operations on the ISS, a unique human-tended test platform and the only test bed within the space environment. The concept is to be validated on the ISS, the only “test bed” on which to prepare for future manned exploration missions. The paper authors believe that early self-diagnostic coupled with autonomous identification of proper preventive responses on negative trends are critical in order to keep astronauts healthy.

Advances in integrated circuit technologies have led to the integration of medical sensor front ends with data processing circuits, i.e., mobile platform design for wearable sensors. We discuss design methodologies for wearable sensor nodes and their applications in m-Health. From the user perspective, flexibility, comfort, appearance, fashion, ease-of-use, and visibility are key form factors. From the technology development point of view, high accuracy, low power consumption, and high signal to noise ratio are desirable features. From the embedded software design standpoint, real time data analysis algorithms, application and database interfaces are the critical components to create successful wearable sensor-based products.

Complementary metal oxide semiconductor (CMOS) technology offers batch manufacturability by ultra-large-scaleintegration (ULSI) of high performance electronics with a performance/cost advantage and profound reliability. However, as of today their focus has been on rigid and bulky thin film based materials. Their applications have been limited to computation, communication, display and vehicular electronics. With the upcoming surge of Internet of Everything, we have critical opportunity to expand the world of electronics by bridging between CMOS technology and free form electronics which can be used as wearable, implantable and embedded form. The asymmetry of shape and softness of surface (skins) in natural living objects including human, other species, plants make them incompatible with the presently available uniformly shaped and rigidly structured today’s CMOS electronics. But if we can break this barrier then we can use the physically free form electronics for applications like plant monitoring for expansion of agricultural productivity and quality, we can find monitoring and treatment focused consumer healthcare electronics – and many more creative applications. In our view, the fundamental challenge is to engage the mass users to materialize their creative ideas. Present form of electronics are too complex to understand, to work with and to use. By deploying game changing additive manufacturing, low-cost raw materials, transfer printing along with CMOS technology, we can potentially stick high quality CMOS electronics on any existing objects and embed such electronics into any future objects that will be made. The end goal is to make them smart to augment the quality of our life. We use a particular example on implantable electronics (brain machine interface) and its integration strategy enabled by CMOS device design and technology run path.

The last 10 years have seen the emergence of two-dimensional (2D) nanomaterials such as graphene, transition metal dichalcogenides (TMDs), and black phosphorus (BP) among the growing portfolio of layered van der Waals thin films. Graphene, the prototypical 2D material has advanced rapidly in device, circuit and system studies that has resulted in commercial large-area applications. In this work, we provide a perspective of the emerging and potential translational applications of 2D materials including semiconductors, semimetals, and insulators that comprise the basic material set for diverse nanosystems. Applications include RF transceivers, smart systems, the so-called internet of things, and neurotechnology. We will review the DC and RF electronic performance of graphene and BP thin film transistors. 2D materials at sub-um channel length have so far enabled cut-off frequencies from baseband to 100GHz suitable for low-power RF and sub-THz concepts.

The flexible electronics industry has adopted flexible hybrid electronic (FHE) systems as a go to market strategy. High volume products are emerging for body worn bio patches, conformal structural appliques and smart labels. These products were principally developed for volume consumer and industrial market solutions but are directly applicable to advanced defense systems. This article highlights the state of the art for bio patch, conformal and smart FHE products and identifies their dual use capability for defense systems. A discussion of the manufacturing base for FHE products is presented and current experimental prototype results and performance are shared.

Epidermal electronics is a class of noninvasive and unobstructive skin-mounted, tattoo-like sensors and electronics capable of vital sign monitoring and establishing human-machine interface. The high cost of manpower, materials, vacuum equipment, and photolithographic facilities associated with its manufacture greatly hinders the widespread use of disposable epidermal electronics. Here we report a cost and time effective, completely dry, benchtop “cut-and-paste” method for the freeform and portable manufacture of multiparametric epidermal sensor systems (ESS) within minutes. This versatile method works for all types of thin metal and polymeric sheets and is compatible with any tattoo adhesives or medical tapes. The resulting ESS are multimaterial and multifunctional and have been demonstrated to noninvasively but accurately measure electrophysiological signals, skin temperature, skin hydration, as well as respiratory rate. In addition, planar stretchable coils exploiting double-stranded serpentine design have been successfully applied as wireless, passive epidermal strain sensors.

This paper will review the origins and state of the art in paper-based electronics, suggesting the stage is set for future promising applications. Current interest in paper-based electronics can trace its roots to recent developments in paper-based microfluidics. With a need to improve the reliability and sensitivity of paperbased microfluidics for certain tasks, there were natural efforts to begin embedding sensing electrodes into microfluidic devices. Recognizing the general benefits of paper as an advanced material (e.g., its environmental friendliness, bendable nature, and low cost), efforts in paper-based electronics also began to take a life of their own with demonstrations of transistors, batteries and devices for energy storage, energy harvesting, sensors to improve situational awareness, acoustics, and displays. The state-of-the-art paper-based electronic devices have benefited and will continue to profit from technologies for printing and transferring electronic functionality onto the surfaces of paper-based substrates. Nonetheless, the authors suggest that many future promising applications will go beyond using paper as a carrier/substrate for electronic components to explore tuning of the electrical, mechanical, and chemical properties of the paper itself. With these technical advances, paper-based electronics will move closer to economically viable killer applications.

Recent advances in soft electronics have attracted great attention, largely due to their potential applications in personalized, bio-integrated healthcare devices. The mechanical mismatch between conventional electronic/optoelectronic devices and soft human tissues/organs have presented many challenges, such as the low signalto- noise ratio of biosensors because of the incomplete integration of rigid devices with the body, inflammation and excessive immune responses of implanted stiff devices originated from friction and their foreign nature to biotic systems, and the considerable discomfort and consequent stress experienced by users when wearing/implanting these devices. Ultra-flexible and stretchable electronic devices are being highlighted due to their low system modulus and the intrinsic system-level softness that are important to solve these issues. Here, we describe our unique strategies for the nanomaterial synthesis and fabrication, their seamless assembly and integration, and the design and development of corresponding wearable healthcare devices and minimally invasive surgical tools. These bioelectronic systems fully utilize recent breakthroughs in unconventional soft electronics based on nanomaterials to address unsolved issues in clinical medicine and to provide new opportunities in the personalized healthcare.

Recent advances in biomedical sciences, especially in the field of human genetics, is increasingly considered to facilitate a new frontier in development of novel disease-modifying therapeutics. One of major challenges in the development of nucleic acid therapeutics is efficient and specific delivery of the molecules to the target tissue and cell upon systemic administration. In this report, I discuss our strategy to develop combinatorial-designed multifunctional nanoparticle assemblies based on natural biocompatible and biodegradable polymers for nucleic acid delivery in: (1) overcoming tumor drug resistance and (2) genetic modulation of macrophage functional phenotype from M1 to M2 in treatment of inflammatory diseases.

"Surface-enhanced Raman spectroscopy" (SERS) nanoparticles have gained much attention in recent years for in silico, in vitro and in vivo sensing applications. Our group has developed novel generations of biocompatible "surfaceenhanced resonance Raman spectroscopy" (SERRS) nanoparticles as novel molecular imaging agents. Via rigorous optimization of the different variables contributing to the Raman enhancement, we were able to design SERRS nanoparticles with so far unprecedented sensitivity of detection under in vivo imaging conditions (femto-attomolar range). This has resulted in our ability to visualize, with a single nanoparticle, many different cancer types (after intravenous injection) in mouse models. The cancer types we have tested so far include brain, breast, esophagus, stomach, pancreas, colon, sarcoma, and prostate cancer. All mouse models used are state-of-the-art and closely mimic the tumor biology in their human counterparts. In these animals, we were able to visualize not only the bulk tumors, but importantly also microscopic extensions and locoregional satellite metastases, thus delineating for the first time the true extent of tumor spread. Moreover, the particles enable the detection of premalignant lesions. Given their inert composition they are expected to have a high chance for clinical translation, where we envision them to have an impact in various scenarios ranging from early detection, image-guidance in open or minimally invasive surgical procedures, to noninvasive imaging in conjunction with spatially offset (SESORS) Raman detection devices.

Success of personalized medicine in cancer therapy depends on the ability to identify and molecularly phenotype tumors. Current clinical imaging techniques cannot be integrated with precision molecular medicine at the level of single cells or microlesions due to limited resolution. In this work we use molecularly targeted infrared emitting optical probes to identify and characterize metastatic microlesions prior to their detection with clinically relevant imaging modalities. These contrast agents form the basis of an in vivo optical imaging system capable of resolving internal microlesions, filling a critical unmet need in cancer imaging.

Micro air vehicles which operate autonomously at low altitude in cluttered environments require a method for onboard obstacle avoidance for safe operation. Previous methods deploy either purely reactive approaches, mapping low-level visual features directly to actuator inputs to maneuver the vehicle around the obstacle, or deliberative methods that use on-board 3-D sensors to create a 3-D, voxel-based world model, which is then used to generate collision free 3-D trajectories. In this paper, we use forward-looking stereo vision with a large horizontal and vertical field of view and project range from stereo into a novel robot-centered, cylindrical, inverse range map we call an egocylinder. With this implementation we reduce the complexity of our world representation from a 3D map to a 2.5D image-space representation, which supports very efficient motion planning and collision checking, and allows to implement configuration space expansion as an image processing function directly on the egocylinder. Deploying a fast reactive motion planner directly on the configuration space expanded egocylinder image, we demonstrate the effectiveness of this new approach experimentally in an indoor environment.

In this work, we provide an overview of vision-based control for perching and grasping for Micro Aerial Vehicles. We investigate perching on at, inclined, or vertical surfaces as well as visual servoing techniques for quadrotors to enable autonomous perching by hanging from cylindrical structures using only a monocular camera and an appropriate gripper. The challenges of visual servoing are discussed, and we focus on the problems of relative pose estimation, control, and trajectory planning for maneuvering a robot with respect to an object of interest. Finally, we discuss future challenges to achieve fully autonomous perching and grasping in more realistic scenarios.

We address the key challenges for autonomous fast flight for Micro Aerial Vehicles (MAVs) in 3-D, cluttered environments. For complete autonomy, the system must identify the vehicle's state at high rates, using either absolute or relative asynchronous on-board sensor measurements, use these state estimates for feedback control, and plan trajectories to the destination. State estimation requires information from different sensors to be fused, exploiting information from different, possible asynchronous sensors at different rates. In this work, we present techniques in the area of planning, control and visual-inertial state estimation for fast navigation of MAVs. We demonstrate how to solve on-board, on a small computational unit, the pose estimation, control and planning problems for MAVs, using a minimal sensor suite for autonomous navigation composed of a single camera and IMU. Additionally, we show that a consumer electronic device such as a smartphone can alternatively be employed for both sensing and computation. Experimental results validate the proposed techniques. Any consumer, provided with a smartphone, can autonomously drive a quadrotor platform at high speed, without GPS, and concurrently build 3-D maps, using a suitably designed app.

In this paper, we propose a visual-inertial state estimation framework which is able to detect and mitigate failure modes to ensure best possible state estimation for platform control at all times. The main focus here is on the proposed sensor switching method which allows seamless switching between integration of pure inertial cues, the use of inertial-optical ow based velocity estimates, and the use of visual-inertial based position estimates for the control of an inherently unstable aerial vehicle. The switching mechanism automatically detects if a state estimator part is faulty and reduces the sensory input to the remaining, healthy, information streams. In addition, a re-initialization sequence is run for the faulty segment until the full system is recovered. With the additional capability of each segment for self-calibration, the system is both self-calibrating and self-healing. The full framework has been integrated on an embedded platform on-board a real 500g small aerial vehicle and run at 30Hz camera stream and 1kHz inertial readings for live demonstration.

Aggressive flight of micro air vehicles (MAVs) in unstructured, GPS-denied environments poses unique challenges for estimation of vehicle pose and velocity due to the noise, delay, and drift in individual sensor measurements. Maneuvering flight at speeds in excess of 5 m/s poses additional challenges even for active range sensors; in the case of LIDAR, an assembled scan of the vehicles environment will in most cases be obsolete by the time it is processed. Multi-sensor fusion techniques which combine inertial measurements with passive vision techniques and/or LIDAR have achieved breakthroughs in the ability to maintain accurate state estimates without the use of external positioning sensors. In this paper, we survey algorithmic approaches to exploiting sensors with a wide range of nonlinear dynamics using filter and bundle-adjustment based approaches for state estimation and optimal control. From this foundation, we propose a biologically-inspired framework for incorporating the human operator in the loop as a privileged sensor in a combined human/autonomy paradigm.

While traditional sensors provide accurate measurements of quantifiable information, humans provide better qualitative information and holistic assessments. Sensor fusion approaches that team humans and machines can take advantage of the benefits provided by each while mitigating the shortcomings. These two sensor sources can be fused together using Bayesian fusion, which assumes that there is a method of generating a probabilistic representation of the sensor measurement. This general framework of fusing estimates can also be applied to joint human-machine decision making. In the simple case, binary decisions can be fused by using a probability of taking an action versus inaction from each decision-making source. These are fused together to arrive at a final probability of taking an action, which would be taken if above a specified threshold. In the case of path planning, rather than binary decisions being fused, complex decisions can be fused by allowing the human and machine to interact with each other. For example, the human can draw a suggested path while the machine planning algorithm can refine it to avoid obstacles and remain dynamically feasible. Similarly, the human can revise a suggested path to achieve secondary goals not encoded in the algorithm such as avoiding dangerous areas in the environment.

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

In support of achieving better performance on autonomous mapping and exploration tasks by incorporating human input, we seek here to first characterize humans’ ability to recognize locations from limited visual information. Such a characterization is critical to the design of a human-in-the-loop system faced with deciding whether and when human input is useful. In this work, we develop a novel and practical place-recognition task that presents humans with video clips captured by a navigating ground robot. Using this task, we find experimentally that human performance does not seem to depend on factors such as clip length or familiarity with the scene and also that there is significant variability across subjects. Moreover, we find that humans significantly outperform a state-of-the-art computational solution to this problem, suggesting the utility of incorporating human input in autonomous mapping and exploration techniques.

With growing use of automation in civilian and military contexts that engage cooperatively with humans, the operator’s level of trust in the automated system is a major factor in determining the efficacy of the human-autonomy teams. Suboptimal levels of human trust in autonomy (TiA) can be detrimental to joint team performance. This mis-calibrated trust can manifest in several ways, such as distrust and complete disuse of the autonomy or complacency, which results in an unsupervised autonomous system. This work investigates human behaviors that may reflect TiA in the context of an automated driving task, with the goal of improving team performance. Subjects performed a simulated leaderfollower driving task with an automated driving assistant. The subjects had could choose to engage an automated lane keeping and active cruise control system of varying performance levels. Analysis of the experimental data was performed to identify contextual features of the simulation environment that correlated to instances of automation engagement and disengagement. Furthermore, behaviors that potentially indicate inappropriate TiA levels were identified in the subject trials using estimates of momentary risk and agent performance, as functions of these contextual features. Inter-subject and intra-subject trends in automation usage and performance were also identified. This analysis indicated that for poorer performing automation, TiA decreases with time, while higher performing automation induces less drift toward diminishing usage, and in some cases increases in TiA. Subject use of automation was also found to be largely influenced by course features.

A novel approach for the fusion of heterogeneous object classification methods is proposed. In order to effectively integrate the outputs of multiple classifiers, the level of ambiguity in each individual classification score is estimated using the precision/recall relationship of the corresponding classifier. The main contribution of the proposed work is a novel fusion method, referred to as Dynamic Belief Fusion (DBF), which dynamically assigns probabilities to hypotheses (target, non-target, intermediate state (target or non-target) based on confidence levels in the classification results conditioned on the prior performance of individual classifiers. In DBF, a joint basic probability assignment, which is obtained from optimally fusing information from all classifiers, is determined by the Dempster's combination rule, and is easily reduced to a single fused classification score. Experiments on RSVP dataset demonstrates that the recognition accuracy of DBF is considerably greater than that of the conventional naive Bayesian fusion as well as individual classifiers used for the fusion.

Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

Soft robotics is a recent and rapidly growing field of research, which aims at unveiling the principles for building robots that include soft materials and compliance in the interaction with the environment, so as to exploit so-called embodied intelligence and negotiate natural environment more effectively. Using soft materials for building robots poses new technological challenges: the technologies for actuating soft materials, for embedding sensors into soft robot parts, for controlling soft robots are among the main ones. This is stimulating research in many disciplines and many countries, such that a wide community is gathering around initiatives like the IEEE TAS TC on Soft Robotics and the RoboSoft CA – A Coordination Action for Soft Robotics, funded by the European Commission. Though still in its early stages of development, soft robotics is finding its way in a variety of applications, where safe contact is a main issue, in the biomedical field, as well as in exploration tasks and in the manufacturing industry. And though the development of the enabling technologies is still a priority, a fruitful loop is growing between basic research and application-oriented research in soft robotics.

Last decade witnessed the revival of fluidic soft actuation. As pressure-operated soft robotics becomes more popular with promising recent results, system integration remains an outstanding challenge. Inspired greatly by biology, we envision future robotic systems to embrace mechanical compliance with bodies composed of soft and hard components as well as electronic and sensing sub-systems, such that robot maintenance starts to resemble surgery. In this vision, portable energy sources and driving infrastructure plays a key role to offer autonomous many-DoF soft actuation. On the other hand, while offering many advantages in safety and adaptability to interact with unstructured environments, objects, and human bodies, mechanical compliance also violates many inherent assumptions in traditional rigid-body robotics. Thus, a complete soft robotic system requires new approaches to utilize proprioception that provides rich sensory information while remaining flexible, and motion control under significant time delay. This paper discusses our proposed solutions for each of these system-level challenges in soft robotics research.

In this paper, we introduce a novel, continuously bending “robot tongue.” The tongue replaces the existing parallel jaw gripper at the end of a KUKA industrial robot manipulator. The resulting system augments the precise positioning of the KUKA with unique capabilities for adaptive grasping afforded by the new robot tongue. We demonstrate the ability of the system to grasp and manipulate objects over a wide range of scales and geometries and evaluate the potential for use of such tongues in various applications.

Infrared spectroscopy has proven to be an excellent tool for identifying and quantifying gases, liquids and solid samples. For many applications, tunable laser based systems are displacing the traditional FTIR spectrometry, which utilizes black body radiators as the sources of broadband infrared radiation. Even though the laser-based systems are generally more expensive and not quite as versatile as the FTIR systems, they provide unique advantages of higher powers, better resolution, speed and a capability for projecting the interrogating light beam over long distances. Being able to project optical radiation over long distances provides infrared spectroscopy a special advantage over all other methods for detection and quantification of remote targets. All other techniques, including mass spectrometry require the instrumentation to be in close proximity of the target being interrogated. Of all laser based spectroscopy schemes, the mid wave infrared (MWIR) and long wave infrared (LWIR) regions have proven to be very effective for laser based systems, because most if not all relevant undesirable targets (gases, liquids and solids) have strong and well characterized absorption signatures in these regions and because, in general, MWIR and LWIR laser radiation is eye safe because of strong absorption by liquid water.

The development of two longwave infrared quantum cascade laser (QCL) based surface contaminant detection platforms supporting government programs will be discussed. The detection platforms utilize reflectance spectroscopy with application to optically thick and thin materials including solid and liquid phase chemical warfare agents, toxic industrial chemicals and materials, and explosives. Operation at standoff (10s of m) and proximal (1 m) ranges will be reviewed with consideration given to the spectral signatures contained in the specular and diffusely reflected components of the signal. The platforms comprise two variants: Variant 1 employs a spectrally tunable QCL source with a broadband imaging detector, and Variant 2 employs an ensemble of broadband QCLs with a spectrally selective detector. Each variant employs a version of the Adaptive Cosine Estimator for detection and discrimination in high clutter environments. Detection limits of 5 μg/cm2 have been achieved through speckle reduction methods enabling detector noise limited performance. Design considerations for QCL-based standoff and proximal surface contaminant detectors are discussed with specific emphasis on speckle-mitigated and detector noise limited performance sufficient for accurate detection and discrimination regardless of the surface coverage morphology or underlying surface reflectivity. Prototype sensors and developmental test results will be reviewed for a range of application scenarios. Future development and transition plans for the QCL-based surface detector platforms are discussed.

This manuscript describes advancements toward a mobile platform for standoff detection of trace explosives on relevant substrates using broadband infrared spectroscopic imaging. In conjunction with this, we are developing a technology for detection based on photo-thermal infrared (IR) imaging spectroscopy (PT-IRIS). PT-IRIS leverages one or more IR quantum cascade lasers (QCL), tuned to strong absorption bands in the analytes and directed to illuminate an area on a surface of interest. An IR focal plane array is used to image the surface thermal emission upon laser illumination. The PT-IRIS signal is processed as a hyperspectral image cube comprised of spatial, spectral and temporal dimensions as vectors within a detection algorithm. Here we describe methods to increase both sensitivity to trace explosives and selectivity between different analyte types by exploiting a broader spectral range than in previous configurations. Previously we demonstrated PT-IRIS at several meters of standoff distance indoors and in field tests, while operating the lasers below the infrared eye-safe intensity limit (100 mW/cm2). Sensitivity to explosive traces as small as a single 10 μm diameter particle (~1 ng) has been demonstrated.

Multi-modal chemical sensors based on microelectromechanical systems (MEMS) have been developed with an electrical readout. Opto-calorimetric infrared (IR) spectroscopy, capable of obtaining molecular signatures of extremely small quantities of adsorbed explosive molecules, has been realized with a microthermometer/microheater device using a widely tunable quantum cascade laser. A microthermometer/microheater device responds to the heat generated by nonradiative decay process when the adsorbed explosive molecules are resonantly excited with IR light. Monitoring the variation in microthermometer signal as a function of illuminating IR wavelength corresponds to the conventional IR absorption spectrum of the adsorbed molecules. Moreover, the mass of the adsorbed molecules is determined by measuring the resonance frequency shift of the cantilever shape microthermometer for the quantitative opto-calorimetric IR spectroscopy. In addition, micro-differential thermal analysis, which can be used to differentiate exothermic or endothermic reaction of heated molecules, has been performed with the same device to provide additional orthogonal signal for trace explosive detection and sensor surface regeneration. In summary, we have designed, fabricated and tested microcantilever shape devices integrated with a microthermometer/microheater which can provide electrical responses used to acquire both opto-calorimetric IR spectra and microcalorimetric thermal responses. We have demonstrated the successful detection, differentiation, and quantification of trace amounts of explosive molecules and their mixtures (cyclotrimethylene trinitramine (RDX) and pentaerythritol tetranitrate (PETN)) using three orthogonal sensing signals which improve chemical selectivity.

We perform active hyperspectral imaging using tunable mid-infrared (MIR) quantum cascade lasers for contactless identification of solid and liquid contaminations on surfaces. By collecting the backscattered laser radiation with a camera, a hyperspectral data cube, containing the spatially resolved spectral information of the scene is obtained. Data is analyzed using appropriate algorithms to find the target substances even on substrates with a priori unknown spectra. Eye-save standoff detection of residues of explosives and precursors over extended distances is demonstrated and the main purpose of our system. Using a MIR EC-QCL with a tuning range from 7.5 μm to 10 μm, detection of a large variety of explosives, e.g. TNT, PETN and RDX and precursor materials such as Ammonium Nitrate could be demonstrated. In a real world scenario stand-off detection over distances of up to 20 m could be successfully performed. This includes measurements in a post blast scenario demonstrating the potential of the technique for forensic investigations.

In this paper, we present the results of long-term operational testing of several quantum cascade laser (QCL) variants to illustrate their robustness and long lifetimes. Performance factors are investigated including power and spectral stability over different timescales ranging from days to years. The effects of burn-in, packaging, mounting, and facet coatings are considered with respect to their influence on long-term laser performance. In addition, the results from the several years’ operation of a custom external cavity quantum cascade laser-based trace gas sensor are presented to highlight the reliable performance of QCL-based sensor systems. This sensor monitored the laboratory air for multiple chemicals and operated continuously for two years without any evidence of degradation in performance. The data from all of these experiments will be discussed to demonstrate the reliability and robust performance of QCLs.

Milliwatt average power terahertz quantum cascade lasers (THz-QCLs, 2 THz to 5 THz) have been developed for spectroscopy and as local oscillators for heterodyne receivers. Novel DFB THz-QCLs have been fabricated and show single-mode operation. The narrow line widths of <10 MHz and stark shift tuning of of 6 GHz, allows for wavelength modulation spectroscopy of low pressure gasses in the unexplored THz frequency band. The same devices also act as local-oscillators for heterodyne receivers for remote-sensing and astronomy. Lastly we report on improved tunable DFB devices for use in spectroscopy.

The author summarizes development of uncooled microbolometer terahertz (THz) focal plane arrays (FPAs) and real-time cameras for sub-THz and THz wave detection. The array formats are 320x240 and 640x480, and the cameras have several functions, such as lock-in imaging, external-trigger imaging, image processing (pixel binning and frame integration), beam profiling and so on. The FPAs themselves are sensitive to sub-THz, THz and infrared radiations. Active imaging systems based on the imagers are described. One of them is a real-time transmission-type THz microscope which contains a THz camera and a quantum cascade laser (QCL). The other one is an active sub-THz imaging system, where a transmission imaging mode and a reflection imaging mode can be switched with one-touch operation. Strong THz emitters, such as far-infrared gas lasers and QCLs, are strongly coherent and often produce interference fringes in an image. A method of reducing the interference fringes (beam homogenizing) is described. Microbolometer FPAs developed by other groups, antenna-coupled CMOS FPA, array detectors based on GaAs high-mobility heterostructure and so on are also summarized, which operate in real-time and at room temperature. A fair method of evaluating performance of detectors with different sizes and at different wavelengths is explained and the performances of the detectors are compared.

Terahertz technology has found numerous applications for the detection of biological and chemical hazardous agents, medical diagnostics, detection of explosives, providing security in buildings, airports, and other public spaces, shortrange covert communications (in the THz and sub-THz windows), and applications in radio astronomy and space research. The expansion of these applications will depend on the development of efficient electronic terahertz sources and sensitive low-noise terahertz detectors. Schottky diode frequency multipliers have emerged as a viable THz source technology reaching a few THz. High speed three terminal electronic devices (FETs and HBTs) have entered the THz range (with cutoff frequencies and maximum frequencies of operation above 1 THz). A new approach called plasma wave electronics recently demonstrated an efficient terahertz detection in GaAs-based and GaN-based HEMTs and in Si MOS, SOI, FINFETs and in FET arrays. This progress in THz electronic technology has promise for a significant expansion of THz applications.

While THz and mm-wave imaging systems provide an interesting avenue for stand-off detection of concealed weapons and other threats without the need for ionizing radiation, there are many physical and technical obstacles which still prevent these systems from becoming commercially practical. This paper introduces the major issues for active and passive imaging including background masking, specular responses, and thermal equalization. Secondly, the paper discusses the prospects of radar imaging, and tradeoffs between system parameters such as transmit power, receiver sensitivity and phase noise, and how these parameters affect corresponding physical behavior including aperture size, resolution, penetration, and stand-off distance.

The ability of millimeter waves (1-10 mm, or 30-300 GHz) to penetrate through dense materials, such as leather, wool, wood and gyprock, and to also transmit over long distances due to low atmospheric absorption, makes them ideal for numerous applications, such as body scanning, building inspection and seeing in degraded visual environments. Current drawbacks of millimeter wave imaging systems are they use single detector or linear arrays that require scanning or the two dimensional arrays are bulky, often consisting of rather large antenna-couple focal plane arrays (FPAs). Previous work from INO has demonstrated the capability of its compact lightweight camera, based on a 384 x 288 microbolometer pixel FPA with custom optics for active video-rate imaging at wavelengths of 118 μm (2.54 THz), 432 μm (0.69 THz), 663 μm (0.45 THz), and 750 μm (0.4 THz). Most of the work focused on transmission imaging, as a first step, but some preliminary demonstrations of reflection imaging at these were also reported. In addition, previous work also showed that the broadband FPA remains sensitive to wavelengths at least up to 3.2 mm (94 GHz). The work presented here demonstrates the ability of the INO terahertz camera for reflection imaging at millimeter wavelengths. Snapshots taken at video rates of objects show the excellent quality of the images. In addition, a description of the imaging system that includes the terahertz camera and different millimeter sources is provided.

Low efficiency of the standard THz-TDS method for the detection and identification of substances is demonstrated. For this purpose, we use a few examples. In the first example, we model the noisy THz signals transmitted through the amphetamine-type stimulant in real conditions. Namely, with a temperature 18° C, the relative humidity of about 50 % and the distance between the parabolic mirror and the object about of 3.5 meters. We show that the standard THz-TDS method reveals the spectral features of many neutral substances and explosives in the noisy THz signals from the illicit stimulant MA, at the same time this method is not able to detect the presence of this stimulant in the noisy signals. The second example is the detection and identification of plastids with inhomogeneous surface in reflection mode. We show that inhomogeneous surface distorts spectral characteristics of the reflected THz signal main pulse, which cannot be used for the detection and identification of the plastids by means of the THz TDS method. In the last example we show that even under laboratory conditions (at short distance from the receiver), THz TDS detects in the semiconductors the absorption frequencies, which belong to both hazardous and neutral substances. To overcome this disadvantage, we propose to use the time-dependent spectrum of the THz pulse, transmitted through or reflected from a substance. For quality assessment of the presence of the standard substance absorption frequency in the signal under analysis, we use time-dependent integral correlation criteria. The influence of aperture placed in front of the sample on spectral properties of silicon wafers with different resistivity is demonstrated as well.

In this paper, we have experimentally demonstrated the engineering of semi-metal single layer CVD Graphene’s bandgap by decorating with randomly distributed ZnO nano-seed grown by sonication of Zinc acetate dehydrate. The proximity of nanoparticles and Graphene breaks Graphene’s sublattice symmetry and opens-up a bandgap. The 2-D/G ratio of Raman spectroscopy of decorated Graphene along with a peak at 432.39 cm-1 confirmed presence of ZnO on single layer Graphene. The introduced bandgap was measured from the slope of Arrhenius plot. Graphene with significant bandgap introduced by the proposed methods could be used for devices intended for digital and logic applications.

Compact and hand-held spectrometers may be very interesting for the measurement of spectral signatures of chemicals or objects. To achieve this goal, ONERA and IPAG have developed a new on chip Fourier Transform Spectrometer operating in the visible spectral range with a high spectral resolution (near 2 cm-1), named visible HR SPOC (visible High Resolution Spectrometer On Chip). It is directly inspired from the MICROSPOC infrared spectrometer, studied at ONERA in the past years. This spectrometer is made of a stair-step two-wave interferometer directly glued on a CMOS detector making it a very compact prototype. After calibrating the optical path difference, measurements of experimental spectra are presented.

Plasmonic nanodevices are metallic structures that exhibit plasmonic effects when exposed to light, causing scattering and enhancement of that light. These plasmons makes it possible for light to be focused below the diffraction limit. Dark-field spectroscopy has been used to capture the scattering spectra of these structures in order to examine the scattering and resonant frequencies of the plasmons provided by the devices. The geometries of the devices change which wavelengths of light are most readily able to couple to the device, resulting in a change in the wavelength of the scattered light. A variety of device geometries and configurations will be studied, including nanodiscs, nanowires, and plasmonic gratings, along with double-width nanogap plasmonic gratings. These new structures will have features below the fabrication limit of electron-beam lithography, i.e. sub-10 nanometer features. The polarization dependencies of these resonance modes are investigated as well. A relation between device geometry and wavelength will be drawn; in effect, this will allow the selection of geometry of the fabricated device based on the desired wavelength of light to be scattered. Preliminary Raman spectroscopy will also be performed in order to study the device response and usefulness for surface-enhanced Raman spectroscopy.

Plasmonic ultraviolet (UV) photodetectors have witnessed ongoing and tremendous enhancements in quantum efficiency and responsivity. Here, we go beyond regular plasmonic detectors by using periodic arrays of fractal aluminum nanostructures as Cayley trees deposited on a Ga2O3 substrate to generate photocurrent. We show that the proposed aluminum Cayley trees are able to support and intensify strong broad plasmon resonant modes across the UV to the visible spectrum. It is shown that the Cayley trees can be tailored to facilitate strong absorption at high energies (short wavelengths), resulting formation of hot carriers. Having perfect compatibility to operate at the UV spectrum, fractal aluminum structures and Ga2O3 substrate help to increase the produced photocurrent remarkably. Presence of Ga2O3 layer blue-shifts the peak of absorption to higher energies and helps to generate hot carriers at deeper UV wavelengths.

Gimbal-less two-axis quasistatic MEMS mirrors have the ability to reflect optical beams to arbitrary positions and with arbitrary velocity. This technology has become established in many applications including laser based tracking, 3D scanning, biomedical imaging, free-space communication, and LiDAR. However, for certain defense applications, the total angle × diameter product, or the mirror’s effective achievable resolution (θ*D product), has not been large enough to address requirements for agile steering in large fields of regard and with a low diffraction-limited beam divergence. Two key limitations have been the relatively low forces available in electrostatic combdrive actuators and the susceptibility of large-diameter MEMS mirrors to shock and vibrations. In this work, we demonstrate that these same MEMS mirrors can have dramatically increased performance when fully immersed and packaged in dielectric liquids with highly favorable torque-increasing, damping-increasing, and optical gain-increasing properties. The rotating electrostatic combdrive has its torque multiplied by liquid’s relative permittivity of ~2.5. Furthermore, by selecting the appropriate fluid viscosity, quality factor of the device is reduced and structural damping is tuned to near critical damping. Finally, the increased scan angle due to the ~1.5-1.7 index of refraction of the fluid is an additional benefit. These numerous benefits of the fluidic packaging enabled us to double and in some cases triple the previously achieved θ*D product of two-axis quasistatic MEMS mirrors while still maintaining speeds applicable for above mentioned applications. One of the most exciting benefits of the packaging methodologies is that the damping dramatically increases shock and vibration tolerance, which will be tested next.

A fiber ring laser which implements hybrid mode locking technique has been proposed and experimentally demonstrated to generate pulse train at 20 GHz repetition rate with ultrashort pulse width. Graphene and charcoal nano-particles acting as passive mode lockers are inserted into a rational harmonic mode-locked fiber laser to improve the performance. With graphene saturable absorbers, the pulse duration is shortened from 5.3 ps to 2.8 ps, and with charcoal nano-particles, it is shortened to 3.2 ps. The RF spectra show that supermode noise can be removed in the presence of the saturable absorbers. Numerical simulation of the pulse transmission has also been carried out, which shows good agreement with the experimental results.

We designed, fabricated, and characterized multi-color IR photodetectors with asymmetrical doping of GaAs/AlGaAs double quantum wells (DQW). We measured and analyzed spectral and noise characteristics to evaluate feasibility of these photodetectors for remote temperature sensing at liquid nitrogen temperatures. The bias voltage controls the charge distribution between the two wells in a DQW unit and provides effective tuning of IR induced electron transitions. We have found that the responsivity of our devices is symmetrical and weakly dependent on the bias voltage because the doping asymmetry compensates the effect of dopant migration in the growth direction. At the same time, the asymmetrical doping strongly enhances the selectivity and tunability of spectral characteristics by bias voltage. Multicolor detection of our QWIP is realized by varying the bias voltage. Maximum detection wavelength moves from 7.5 μm to 11.1 μm by switching applied bias from -5 V to 4 V. Modeling shows significant dependence of the photocurrent ratio on the object temperature regardless of its emissivity and geometrical factors. We also experimentally investigated the feasibility of our devices for remote temperature sensing by measuring the photocurrent as a response to blackbody radiation with the temperature from 300°C to 1000°C in the range of bias voltages from -5 V to 5 V. The agreement between modelling and experimental results demonstrates that our QWIP based on asymmetrically doped GaAs/AlGaAs DQW nanomaterial is capable of remote temperature sensing. By optimizing the physical design and varying the doping level of quantum wells, we can generalize this approach to higher temperature measurements. In addition, continuous variation of bias voltage provides fast collection of large amounts of photocurrent data at various biases and improves the accuracy of remote temperature measurements via appropriate algorithm of signal processing.